Anaconda vs. Jupyter Notebook vs. Strategy Analytics

I have asked all my juniors to work with Anaconda and Pycharm only, as this is the best combination for now. Coming to use cases: 1. When you have multiple applications using multiple Python variants, it is a really good tool instead of Venv (I never like it). 2. If you have to work on multiple tools and you are someone who needs to work on data analytics, development, and machine learning, this is good. 3. If you have to work with both R and Python, then also this is a good tool, and it provides support for both.

Incentivized

I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.

Incentivized

MSTR is great for any organization that is looking for a way to deliver complicated data in an uncomplicated way. From business teams to marketing and finance, several departments benefit from using MSTR to keep track of KPIs enabling teams to make optimizations along the way. MSTR provides great visual representations of data enabling team members to distill thousands of data points into easily digestible charts and graphs

Incentivized

• Anaconda is a one-stop destination for important data science and programming tools such as Jupyter, Spider, R etc.
• Anaconda command prompt gave flexibility to use and install multiple libraries in Python easily.
• Jupyter Notebook, a famous Anaconda product is still one of the best and easy to use product for students like me out there who want to practice coding without spending too much money.

Incentivized

• Simple and elegant code writing ability. Easier to understand the code that way.
• The ability to see the output after each step.
• The ability to use ton of library functions in Python.
• Easy-user friendly interface.

Incentivized

• They sell the product well, and make promises you will actually believe
• "checks the box" for most features a company would need. Doesn't actually deliver them though
• They answer the phone in a timely manner. Can't answer your questions or provide support, but the queue time isn't bad
• They have online documentation. It's not up to date, and likely doesn't reflect the version of software you are using, but hey... they can point to it.

• It can have a cloud interface to store the work.
• Compatible for large size files.
• I used R Studio for building Machine Learning models, Many times when I tried to run the entire code together the software would crash. It would lead to loss of data and changes I made.

Incentivized

• Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
• Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.

Incentivized

• The graph options are not as robust as an Excel user might want.
• The metadata layer can sometimes be slower, and it takes a long time for reports to run.
• Viewing the data feed entered can be cumbersome at times, in terms of validation with reports.

Incentivized

It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.

Incentivized

I would always choose to renew MicroStrategy as long as they lead the market in features, functionality and price. The support of MicroStrategy is timely and professional, I frequently get answers to my questions within 24 hours and normally have solutions within 48 hours. Training available for MicroStrategy completely covers everything required to be able to expertly use MicroStrategy and understand data warehousing.

Incentivized

I am giving this rating because I have been using this tool since 2017, and I was in college at that time. Initially, I hesitated to use it as I was not very aware of the workings of Python and how difficult it is to manage its dependency from project to project. Anaconda really helped me with that. The first machine-learning model that I deployed on the Live server was with Anaconda only. It was so managed that I only installed libraries from the requirement.txt file, and it started working. There was no need to manually install cuda or tensor flow as it was a very difficult job at that time. Graphical data modeling also provides tools for it, and they can be easily saved to the system and used anywhere.

Incentivized

Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.

Incentivized

The standard grid reporting could look more like the styling and object used for the Import and Visual Insight products. In addition, object properties almost seem to be hidden when first using the product. It's as if they are asking the engineers to only use the presets we make available...and, these presets are 10+ years old. On the positive side, Microstrategy seems to be the only product, not named Cognos, which can scale to Big Data. The product is "hackable" via the SDK or tricking the Intelligence Server to do uncommon things. The Microstrategy development team also seems to be very involved with their OEM partners; especially when it comes to features and enhancements. A large majority of the improvements we suggested have made it into the product or on the roadmap for future enhancements. Only suckas fall for the shiny objects from most other vendors; Microstrategy is really the only choice for Enterprise BI.

I've never had an issue with MicroStrategy not being available due to MicroStrategy application malfunction. It is very robust and only failures I've seen were due to user error or the platform the machine running the service failed some how.

Incentivized

Being able to customize the performance based on the business need is extremely powerful. Proper configuration and understanding of the usage pattern is key, if the technical ability of the architect is not at top level, then the product will not be configured correctly which will lead to poor performance.

Incentivized

Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.

Incentivized

I haven't had a need to contact support. However, all required help is out there in public forums.

Incentivized

Good user community. Support team is available if you are under AMC. You get decent support after raising the support ticket. If it is product bug they will inform you and let you know which patch will resolve the same.

Incentivized

I have attended many trainings offered by MicroStrategy; both distance and in-person training. I earned my CRD (Certified Report Developer) certification via the online training. I found the training to be well organized and concise. Overall I will definitely continue to increase my knowledge with MicroStrategy via the online training offering.

We measured following KPI for the success

• Increase in Business Feeds Loads
• Reduction in Controllers Manual Work.
• Conversion of Manual Work into Systematic Workflows.
• Increase in Customer Spend
• Reduction in Service costs
• Reduction in time-to-market for new campaigns
• Increase in cross sell and Up sell
• Error reduction in customer Identification
• Existing client retained

Incentivized

I have experience using RStudio oustide of Anaconda. RStudio can be installed via anaconda, but I like to use RStudio separate from Anaconda when I am worin in R. I tend to use Anaconda for python and RStudio for working in R. Although installing libraries and packages can sometimes be tricky with both RStudio and Anaconda, I like installing R packages via RStudio. However, for anything python-related, Anaconda is my go to!

Incentivized

With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.

Incentivized

Tableau is probably MicroStrategy Analytic's biggest competitor I've noticed over time, and I'm not sure why. Tableau only covers visualizations independently for each business user, which then creates the issues of every employee creating their own version of the data, and then you have 20 versions of the truth. A enterprise data warehouse and MicroStrategy's Visual Insight is a better method.

Incentivized

This software is extremely scaleable, one can add more core servers which performs as a load balancing. The configurations available to manage usage patterns and daily activity are as high a caliber as any other enterprise level software. This product can be installed on both a windows and unix platform allow for integration on a budget.

Incentivized

• It has helped our organization to work collectively faster by using Anaconda's collaborative capabilities and adding other collaboration tools over.
• By having an easy access and immediate use of libraries, developing times has decreased more than 20 %
• There's an enormous data scientist shortage. Since Anaconda is very easy to use, we have to be able to convert several professionals into the data scientist. This is especially true for an economist, and this my case. I convert myself to Data Scientist thanks to my econometrics knowledge applied with Anaconda.

Incentivized

• Positive impact: flexible implementation on any OS, for many common software languages
• Positive impact: straightforward duplication for adaptation of workflows for other projects
• Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration

Incentivized

• MicroStrategy was helpful for reducing the amount of time we needed to spend number crunching large data sets, and in doing so, allowed me as the primary users to spend more time gleaning insights from the data that in turn informed our leadership team to make strategic decisions.
• By creating numerous canned reports available to all members of the team through email distribution or basic access to the platform, we were able to reduce the time I spent showing people how to pull the data in Microsoft Excel by nearly 40% .
• We ended up needing to make many changes to the way our DMP was feeding data into MicroStrategy due to incorrect reporting that caused complications in accounting and finance.